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Healthcare Consultancy System

Author

Listed:
  • Asma Mokashi
  • Pratik Rughe
  • Yashashri Malvi
  • Neha Ghodekar

Abstract

Under the present situation, the healthcare delivery system is prohibitively expensive, inefficient, and unsustainable. Machine Learning (ML) has revolutionized the way businesses and individuals use data to increase system performance. Strategists can work with a range of organized, non - structured, and semi-structured data using machine learning algorithms. This device provides a virtual assistant who can converse with patients in their native language to understand their symptoms, recommend doctors, and monitor health metrics. To process users' complaints and find the closest doctor who can help handle the user's case, the solution relies on natural language processing models and machine learning analytic methodology. A deep bilinear similarity model is also proposed by the framework to boost the generated SQL queries used for predictions and algorithms. BERT and SQLOVA models are used to train the device data collection.

Suggested Citation

  • Asma Mokashi & Pratik Rughe & Yashashri Malvi & Neha Ghodekar, 2021. "Healthcare Consultancy System," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 7(3), pages 439-443, June.
    • Handle: RePEc:jbh:ijsrcs:v7:y2021:i3:id:hcseit217395
    DOI: 10.32628/CSEIT217395
    Note: Article URL: https://ijsrcseit.com/CSEIT217395
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